Biblio
Cloud computing denotes an IT infrastructure where data and software are stored and processed remotely in a data center of a cloud provider, which are accessible via an Internet service. This new paradigm is increasingly reaching the ears of companies and has revolutionized the marketplace of today owing to several factors, in particular its cost-effective architectures covering transmission, storage and intensive data computing. However, like any new technology, the cloud computing technology brings new problems of security, which represents the main restrain on turning to this paradigm. For this reason, users are reluctant to resort to the cloud because of security and protection of private data as well as lack of trust in cloud service providers. The work in this paper allows the readers to familiarize themselves with the field of security in the cloud computing paradigm while suggesting our contribution in this context. The security schema we propose allowing a distant user to ensure a completely secure migration of all their data anywhere in the cloud through DNA cryptography. Carried out experiments showed that our security solution outperforms its competitors in terms of integrity and confidentiality of data.
Data Deduplication provides lots of benefits to security and privacy issues which can arise as user's sensitive data at risk of within and out of doors attacks. Traditional secret writing that provides knowledge confidentiality is incompatible with knowledge deduplication. Ancient secret writing wants completely different users to encode their knowledge with their own keys. Thus, identical knowledge copies of completely different various users can result in different ciphertexts that makes Deduplication not possible. Convergent secret writing has been planned to enforce knowledge confidentiality whereas creating Deduplication possible. It encrypts/decrypts a knowledge copy with a confluent key, that is obtained by computing the cryptographical hash price of the content of the information copy. Once generation of key and encryption, the user can retain the keys and send ciphertext to cloud.
The Internet of Things (IoT) era envisions billions of interconnected devices capable of providing new interactions between the physical and digital worlds, offering new range of content and services. At the fundamental level, IoT nodes are physical devices that exist in the real world, consisting of networking, sensor, and processing components. Some application examples include mobile and pervasive computing or sensor nets, and require distributed device deployment that feed information into databases for exploitation. While the data can be centralized, there are advantages, such as system resiliency and security to adopting a decentralized architecture that pushes the computation and storage to the network edge and onto IoT devices. However, these devices tend to be much more limited in computation power than traditional racked servers. This research explores using the Cassandra distributed database on IoT-representative device specifications. Experiments conducted on both virtual machines and Raspberry Pi's to simulate IoT devices, examined latency issues with network compression, processing workloads, and various memory and node configurations in laboratory settings. We demonstrate that distributed databases are feasible on Raspberry Pi's as IoT representative devices and show findings that may help in application design.
Real world applications of Wireless Sensor Networks such as border control, healthcare monitoring and target tracking require secure communications. Thus, during WSN setup, one of the first requirements is to distribute the keys to the sensor nodes which can be later used for securing the messages exchanged between sensors. The key management schemes in WSN secure the communication between a pair or a group of nodes. However, the storage capacity of the sensor nodes is limited which makes storage requirement as an important parameter for the evaluation of key management schemes. This paper classifies the existing key management schemes proposed for WSNs into three categories: storage inefficient, storage efficient and highly storage efficient key management schemes.